package uiao.com.stream;



    /*
     * Licensed to the Apache Software Foundation (ASF) under one or more
     * contributor license agreements. See the NOTICE file distributed with
     * this work for additional information regarding copyright ownership.
     * The ASF licenses this file to You under the Apache License, Version 2.0
     * (the "License"); you may not use this file except in compliance with
     * the License. You may obtain a copy of the License at
     *
     *    http://www.apache.org/licenses/LICENSE-2.0
     *
     * Unless required by applicable law or agreed to in writing, software
     * distributed under the License is distributed on an "AS IS" BASIS,
     * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
     * See the License for the specific language governing permissions and
     * limitations under the License.
     */

import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.common.serialization.Serdes;
import org.apache.kafka.streams.KafkaStreams;
import org.apache.kafka.streams.StreamsBuilder;
import org.apache.kafka.streams.StreamsConfig;
import org.apache.kafka.streams.Topology;
import org.apache.kafka.streams.kstream.KStream;
import org.apache.kafka.streams.kstream.KTable;
import org.apache.kafka.streams.kstream.Produced;

import java.io.FileInputStream;
import java.io.IOException;
import java.util.Arrays;
import java.util.Locale;
import java.util.Properties;
import java.util.concurrent.CountDownLatch;

    /**
     * Demonstrates, using the high-level KStream DSL, how to implement the WordCount program
     * that computes a simple word occurrence histogram from an input text.
     * <p>
     * In this example, the input stream reads from a topic named "streams-plaintext-input", where the values of messages
     * represent lines of text; and the histogram output is written to topic "streams-wordcount-output" where each record
     * is an updated count of a single word.
     * <p>
     * Before running this example you must create the input topic and the output topic (e.g. via
     * {@code bin/kafka-topics.sh --create ...}), and write some data to the input topic (e.g. via
     * {@code bin/kafka-console-producer.sh}). Otherwise you won't see any data arriving in the output topic.
     */
    public final class WordCountDemo {

        public static final String INPUT_TOPIC = "streams-plaintext-input";
        public static final String OUTPUT_TOPIC = "streams-wordcount-output02";

        static Properties getStreamsConfig(final String[] args) throws IOException {
            final Properties props = new Properties();
            if (args != null && args.length > 0) {
                try (final FileInputStream fis = new FileInputStream(args[0])) {
                    props.load(fis);
                }
                if (args.length > 1) {
                    System.out.println("Warning: Some command line arguments were ignored. This demo only accepts an optional configuration file.");
                }
            }
            props.putIfAbsent(StreamsConfig.APPLICATION_ID_CONFIG, "streams-wordcount1");
            props.putIfAbsent(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
            props.putIfAbsent(StreamsConfig.CACHE_MAX_BYTES_BUFFERING_CONFIG, 0);
            props.putIfAbsent(StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.String().getClass().getName());
            props.putIfAbsent(StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG, Serdes.String().getClass().getName());

            // setting offset reset to earliest so that we can re-run the demo code with the same pre-loaded data
            // Note: To re-run the demo, you need to use the offset reset tool:
            // https://cwiki.apache.org/confluence/display/KAFKA/Kafka+Streams+Application+Reset+Tool
            props.putIfAbsent(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
            return props;
        }

        static void createWordCountStream(final StreamsBuilder builder) {
            final KStream<String, String> source = builder.stream(INPUT_TOPIC);

            final KTable<String, Long> counts = source
                    .flatMapValues(value -> Arrays.asList(value.toLowerCase(Locale.getDefault()).split("\\W+")))
                    .groupBy((key, value) -> value)
                    .count();

            // need to override value serde to Long type
            counts.toStream().to(OUTPUT_TOPIC, Produced.with(Serdes.String(), Serdes.Long()));
        }

        public static void main(final String[] args) throws IOException {
            final Properties props = getStreamsConfig(args);

            final StreamsBuilder builder = new StreamsBuilder();


            final Topology topology = builder.build();
            System.out.println(topology.describe());


            createWordCountStream(builder);
            final KafkaStreams streams = new KafkaStreams(builder.build(), props);
            final CountDownLatch latch = new CountDownLatch(1);

            // attach shutdown handler to catch control-c
            Runtime.getRuntime().addShutdownHook(new Thread("streams-wordcount-shutdown-hook") {
                @Override
                public void run() {
                    streams.close();
                    latch.countDown();
                }
            });

            try {
                streams.start();
                latch.await();
            } catch (final Throwable e) {
                System.exit(1);
            }
            System.exit(0);
        }
    }

